A machine-learning approach to setting optimal thresholds and its application in rolling bearing fault diagnosis
Yao-Chi Tang,
Kuo-Hao Li
Abstract:Bearings are one of the critical components of any mechanical equipment. They induce most equipment faults, and their health status directly impacts the overall performance of equipment. Therefore, effective bearing fault diagnosis is essential, as it helps maintain the equipment stability, increasing economic benefits through timely maintenance. Currently, most studies focus on extracting fault features, with limited attention to establishing fault thresholds. As a result, these thresholds are challenging to … Show more
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